Initiative details
The aim of determining fitness to drive is to achieve a balance between minimising any driving-related road safety risks for the individual and the community and maintaining the driver’s lifestyle and employment-related mobility independence. Driving a car is a complex and dynamic task and there is a wide range of conditions that temporarily affect the ability to drive safely like consuming substances or fatigue. Professional drivers are particularly affected by fatigue. The main effect of fatigue is a progressive withdrawal of attention from the road and traffic demands leading to impaired driving performance. The particular practice of professional drivers include working long hours, prolonged night work, working irregular hours, little or poor sleep, and early starting times which in many cases lead to fatigue. Fatigue causes reduced alertness, longer reaction times, memory problems, poorer psychometric coordination, and less efficient information processing. The results of different surveys world-wide show that over 50% of long-haul drivers have at some time almost fallen asleep at the wheel.
Initiative date
to
Who was/is your target audience?
Policy makers
Public authorities
Company employees
Fleet operators
Car drivers – professional
Educational staff
Public transport
Van drivers
Lorry/truck drivers
Topic
Create awareness
Improve vehicles and infrastructure
Provide alternative solutions
Training
Organisation details
ITCL Technology Centre
School / Research centre
Spain
Burgos
Contact name
Marteyn van Gasteren
Telephone number
+34 947298471
marteyn.vangasteren@itcl.es
Website link
Project activities
If you work together with external partners, list the most important partners and briefly describe their role.
Sapienza University of Rome, IT - Biophysical and behavioural research
Mälardalens University MDU, SE - AI and machine learning, vehicular data research
European Professional Driver Association EPDA, IE - Usability, end-user insights, impact
Association for Road Safety Professionals AIPSS, IT - Pilots lead, impact
European Driving Schools Association EFA, BE - Training, impact
Advanticsys, ES - Cloud platform for vehicle monitoring, data collection device
Securetec, DE - Portable drug screening device
Aselsan, TR - Smart tachograph, roadside control communication
Mälardalens University MDU, SE - AI and machine learning, vehicular data research
European Professional Driver Association EPDA, IE - Usability, end-user insights, impact
Association for Road Safety Professionals AIPSS, IT - Pilots lead, impact
European Driving Schools Association EFA, BE - Training, impact
Advanticsys, ES - Cloud platform for vehicle monitoring, data collection device
Securetec, DE - Portable drug screening device
Aselsan, TR - Smart tachograph, roadside control communication
Please describe the project activities you carried/are carrying out and the time period over which these were implemented.
The FitDrive project was conceived to identify and prevent driving stress states for professional drivers (and consequently driving fitness) with artificial intelligence and machine learning techniques able to build a “usual" driving profile of each driver after some thousands of kms driven. Once the "usual" driving profile of a specific driver has been defined, the AI system is able to detect “unusual” behaviour (outside the "usual" range of parameters) and associate them with the most probable causes, such as fatigue, or other cognitive disorders. The behavioural function consists of a set of indicators representing the range of usual driving behaviour for each specific driver, which will be defined by the self-learning system during a period of ordinary driving. Deviations are determined by the comparison between daily driving results and the personal “usual” profile.
The concept FitDrive system provides a continuous screening of the driver's psychophysical capabilities, alerting him or her to potential impairment on the way: in fact, the abnormal variations detected by the Artificial Intelligence can be associated with early situations of sickness that are not yet apparent to the subject but are about to manifest. The system will continuously learn and adapt itself to the driver: this means that the more a subject drives, the more the system adapts to him/her and the more it is able to make precise detection of anomalies, and the system will also be able to follow changes in driving habits.
The concept FitDrive system provides a continuous screening of the driver's psychophysical capabilities, alerting him or her to potential impairment on the way: in fact, the abnormal variations detected by the Artificial Intelligence can be associated with early situations of sickness that are not yet apparent to the subject but are about to manifest. The system will continuously learn and adapt itself to the driver: this means that the more a subject drives, the more the system adapts to him/her and the more it is able to make precise detection of anomalies, and the system will also be able to follow changes in driving habits.
In terms of implementation, what worked well and what challenges did you need to overcome?
With only 30 days of unsupervised AI learning in the pilots, in vans and trucks, the FitDrive system detected driver states with 84% accuracy.
The FitDrive pilots positively tested the possibility for roadside patrol officers to interrogate the vehicle wirelessly and thus focus on those vehicles that have shown recent “unusual” behaviour, making inspections more efficient and reducing the time that vehicles remain stationary. A further reduction of the controls' time will be achieved through a new and faster drugs screening method.
For fitness-to-drive and fatigue detection to be homogeneous across the different systems and to allow for authorities to intervene, it is necessary to create regulation that defines standard levels of fitness. The FitDrive system allows for this, correlating vehicular data to the driver's biological indicators of reduced fitness to drive.
Another requirement is updated regulation making more vehicle data mandatorily available over the OBD-II port, avoiding proprietary protocols hindering data access. FitDrive has put large effort in awareness raising concerning these matters, through various channels including three meetings at the European Parliament.
The FitDrive pilots positively tested the possibility for roadside patrol officers to interrogate the vehicle wirelessly and thus focus on those vehicles that have shown recent “unusual” behaviour, making inspections more efficient and reducing the time that vehicles remain stationary. A further reduction of the controls' time will be achieved through a new and faster drugs screening method.
For fitness-to-drive and fatigue detection to be homogeneous across the different systems and to allow for authorities to intervene, it is necessary to create regulation that defines standard levels of fitness. The FitDrive system allows for this, correlating vehicular data to the driver's biological indicators of reduced fitness to drive.
Another requirement is updated regulation making more vehicle data mandatorily available over the OBD-II port, avoiding proprietary protocols hindering data access. FitDrive has put large effort in awareness raising concerning these matters, through various channels including three meetings at the European Parliament.
Evaluation
Please summarise how you have evaluated the initiative’s impact (e.g. social media reach, survey, feedback forms, statistics).
Impact was evident from the great interest in FitDrive results from policy makers, authorities and industry, some examples are:
Two Members of the European Parliament received project representatives in the Parliament in three events get informed on recommendations on standardising levels of fitness to drive. The FitDrive system allows for determining generic objective measures, instead of the heterogeneous criteria OEMs use currently.
The EC was much interested in the challenges on obtaining data through the OBD-II port, upon which a recommendation was issued to the corresponding authorities. The EC invited FitDrive to showcase technology at their booth at the TRA2025.
A stakeholder event attracted the Irish Minister of State for Transport, the deputy head of Road Transport of DG MOVE from the EC, among others.
An online workshop on standardisation of fatigue was attended by over 100 professionals.
The Irish Road Safety Authority assisted to the pilots in Ireland.
Several companies, from transport companies to tech start-ups inquired on implementation, data and other results.
Two Members of the European Parliament received project representatives in the Parliament in three events get informed on recommendations on standardising levels of fitness to drive. The FitDrive system allows for determining generic objective measures, instead of the heterogeneous criteria OEMs use currently.
The EC was much interested in the challenges on obtaining data through the OBD-II port, upon which a recommendation was issued to the corresponding authorities. The EC invited FitDrive to showcase technology at their booth at the TRA2025.
A stakeholder event attracted the Irish Minister of State for Transport, the deputy head of Road Transport of DG MOVE from the EC, among others.
An online workshop on standardisation of fatigue was attended by over 100 professionals.
The Irish Road Safety Authority assisted to the pilots in Ireland.
Several companies, from transport companies to tech start-ups inquired on implementation, data and other results.
What has been the effect of the activities?
Fitness to drive is one of the focus points of the new provisional EU Driving Licence rules announced 25 March 2025; FitDrive actively contributed to the preparation of this new directive in two Driving Licence Directive meetings at the European Parliament. This new Directive should improve road safety for every European obtaining a driving licence once it enters into force, an estimated 10 million people per year.
Please briefly explain why your initiative is a good example of improving road safety.
The FitDrive strategy was to focus on transcendent impact by quantifying fitness to drive with easy-to-measure vehicular data, allowing for legislation to define the thresholds beyond which: i) An alert is issued to the driver; ii) The driver is firmly invited to stop and check her/his status (threshold that could be used in legislation for police controls); iii) The SAE3 system is informed that the driver is not deemed capable of responding to an intervention request.
How have you shared information about your project and its results?
The dissemination activities reached out to thousands professionals and civilians through events and European and national level, social media with hundreds of followers, national and regional press, and 23 scientific publications.
The anonymised pilot data will be available on open-access repository Zenodo in 2026.
The methodology and results is being made publicly available in order to encourage the automotive industry to implement it in OEM fatigue detection systems.
The anonymised pilot data will be available on open-access repository Zenodo in 2026.
The methodology and results is being made publicly available in order to encourage the automotive industry to implement it in OEM fatigue detection systems.
